3D object identification based on matchings between a single image and a model
Luc-Henri Pampagnin, Michel Devy · 2002
A model-based method for identifying convex or nonconvex polyhedral objects from a single image is described. An object is known by a region-edge-vertex model and an aspect graph. A few hypotheses are searched in a topological compatibility graph in which each node corresponds to a matching between chains of segments extracted from the image and model faces. The construction of this graph depends only on qualitative or topological criteria (number of edges for a face, syntactic description, perceptual organization, visibility, etc.). The search for hypotheses in the graph relies on the maximal cliques technique modified to deal with the global topological compatibility.>